Tag Archives: Social Science

Sanctimonious Econ Critics

The New Yorker review of Elephant in the Brain raved about Cents and Sensibility, by Gary Morson and Morton Shapiro, a book said to confirm that “intellectual overextension is often found in economics.” Others have similarly raved. But I don’t care much for this book, so let me explain why. (Be warned: this post is LONG.)

In its first sentence, the book declares its aim:

This book creates a dialogue between two fields that rarely have anything to say to each other: economics and the humanities. We mean to show how that dialogue could be conducted and why it has a great deal to contribute. (p.1)

Morson and Shapiro seem to want the sort of “dialogue” where one side talks and the other just listens. All but one chapter elaborates how economists should listen to the humanities, and the one remaining chapter is on how some parts of the humanities should listen to another part, not to economists. There’s only a two page section near the end on “What Humanists Can Learn From Economists,” which even then can’t resist talking more about what economists can learn:

Economists could learn from humanists the complexity of ethical issues, the need for stories, the importance of empathy, and the value of unformalizable good judgement. But humanists could also learn from economists how to think about scarce resources, about the nature of efficiency, and the importance of rational decision making. (p.261)

So what exactly can we economists learn? Continue reading "Sanctimonious Econ Critics" »

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Economists Rarely Say “Nothing But”

Imagine someone said:

Those physicists go too far. They say conservation of momentum applies exactly at all times to absolutely everything in the universe. And yet they can’t predict whether I will raise my right or left hand next. Clearly there is more going on than their theories can explain. They should talk less and read more literature. Maybe then they’d stop saying immoral things like Earth’s energy is finite.

Sounds silly, right? But many literary types really don’t like economics (in part due to politics), and they often try to justify their dislike via a similar critique. They say that we economists claim that complex human behavior is “nothing but” simple economic patterns. For example, in the latest New Yorker magazine, journalist and novelist John Lanchester tries to make such a case in an article titled:

Can Economists and Humanists Ever Be Friends? One discipline reduces behavior to elegantly simple rules; the other wallows in our full, complex particularity. What can they learn from each other?

He starts by focusing on our book Elephant in the Brain. He says we make reasonable points, but then go too far:

The issue here is one of overreach: taking an argument that has worthwhile applications and extending it further than it usefully goes. Our motives are often not what they seem: true. This explains everything: not true. … Erving Goffman’s “The Presentation of Self in Everyday Life,” or … Pierre Bourdieu’s masterpiece “Distinction” … are rich and complicated texts, which show how rich and complicated human difference can be. The focus on signalling and unconscious motives in “The Elephant in the Brain,” however, goes the other way: it reduces complex, diverse behavior to simple rules.

This intellectual overextension is often found in economics, as Gary Saul Morson and Morton Schapiro explain in their wonderful book “Cents and Sensibility: What Economics Can Learn from the Humanities” (Princeton). … Economists tend to be hedgehogs, forever on the search for a single, unifying explanation of complex phenomena. They love to look at a huge, complicated mass of human behavior and reduce it to an equation: the supply-and-demand curves; the Phillips curve … or mb=mc. … These are powerful tools, which can be taken too far.

You might think that Lanchester would support his claim that we overreach by pointing to particular large claims and then offering evidence that they are false in particular ways. Oddly, you’d be wrong. (Our book mentions no math nor rules of any sort.) He actually seems to accept most specific claims we make, even pretty big ones:

Many of the details of Hanson and Simler’s thesis are persuasive, and the idea of an “introspective taboo” that prevents us from telling the truth to ourselves about our motives is worth contemplating. … The writers argue that the purpose of medicine is as often to signal concern as it is to cure disease. They propose that the purpose of religion is as often to enhance feelings of community as it is to enact transcendental beliefs. … Some of their most provocative ideas are in the area of education, which they believe is a form of domestication. … Having watched one son go all the way through secondary school, and with another who still has three years to go, I found that account painfully close to the reality of what modern schooling is like.

While Lanchester does argue against some specific claims, these are not claims that we actually made. For example:

“The Elephant in the Brain”… has moments of laughable wrongness. We’re told, “Maya Angelou … managed not to woo Bill Clinton with her poetry but rather to impress him—so much so that he invited her to perform at his presidential inauguration in 1993.” The idea that Maya Angelou’s career amounts to nothing more than a writer shaking her tail feathers to attract the attention of a dominant male is not just misleading; it’s actively embarrassing.

But we said nothing like “Angelou’s career amounts to nothing more than.” Saying that she impressed Clinton with her poetry is not remotely to imply there was “nothing more” to her career. Also:

More generally, Hanson and Simler’s emphasis on signalling and unconscious motives suggests that the most important part of our actions is the motives themselves, rather than the things we achieve. … The last sentence of the book makes the point that “we may be competitive social animals, self-interested and self-deceived, but we cooperated our way to the god-damned moon.” With that one observation, acknowledging that the consequences of our actions are more important than our motives, the argument of the book implodes.

We emphasize “signalling and unconscious motives” because is the topic of our book. We don’t ever say motives are the most important part of our actions, and as he notes, in our conclusion we suggest the opposite. Just as a book on auto repair doesn’t automatically claim auto repair to be the most important thing in the world, a book on hidden motives needn’t claim motives are the most important aspect of our lives. And we don’t.

In attributing “overreach” to us, Lanchester seems to rely most heavily on a quick answer I gave in an interview, where Tyler Cowen asked me to respond “in as crude or blunt terms as possible”:

Wait, though—surely signalling doesn’t account for everything? Hanson … was asked to give a “short, quick and dirty” answer to the question of how much human behavior “ultimately can be traced back to some kind of signalling.” His answer: “In a rich society like ours, well over ninety per cent.” … That made me laugh, and also shake my head. … There is something thrilling about the intellectual audacity of thinking that you can explain ninety per cent of behavior in a society with one mental tool.

That quote is not from our book, and is from a context where you shouldn’t expect it to be easy to see exactly what was meant. And saying that a signaling motive is on average one of the strongest (if often unconscious) motives in an area of life is to say that this motive importantly shapes some key patterns of behavior in this area of life; it is not remotely to claim that this fact explains most of details of human behavior in this area! So shaping key patterns in 90% of areas explains far less than 90% of all behavior details. Saying that signaling is an important motive doesn’t at all say that human behavior is “nothing more” than signaling. Other motives contribute, we vary in how honest and conscious we are of each motive, there are usually a great many ways to signal any given thing in any given context, and many different cultural equilibria can coordinate individual behavior. There remains plenty of room for complexity, as people like Goffman and Bourdieu illustrate.

Saying that an abstraction is important doesn’t say that the things to which it applies are “nothing but” that abstraction. For example, conservation of momentum applies to all physical behavior, yet it explains only a tiny fraction of the variance in behavior of physical objects. Natural selection applies to all species, yet most species details must be explained in other ways. If most roads try to help people get from points A to B, that simple fact is far from sufficient to predict where all the roads are. The fact that a piece of computer code is designed help people navigate roads explains only a tiny fraction of which characters are where in the code. Financial accounting applies to nearly 100% of firms, yet it explains only a small fraction of firm behavior. All people need air and food to survive, and will have a finite lifespan, and yet these facts explain only a tiny fraction of their behavior.

Look, averaging over many people and contexts there must be some strongest motive overall. Economists might be wrong about what that is, and our book might be wrong. But it isn’t overreach or oversimplification to make a tentative guess about it, and knowing that strongest motive won’t let you explain most details of human behavior. As an analogy, consider that every nation has a largest export commodity. Knowing this commodity will help you understand something about this nation, but it isn’t remotely reasonable to say that a nation is “nothing more” than its largest export commodity, nor to think this fact will explain most details of behavior in this nation.

There are many reasonable complaints one can make about economics. I’ve made many myself. But this complaint that we “overreach” by “reducing complexity to simple rules” seems to me mostly rhetorical flourish without substance. For example, most models we fit to data have error terms to accommodate everything else that we’ve left out of that particular model. We economists are surely wrong about many things, but to argue that we are wrong about a particular thing you’ll actually need to talk about details related to that thing, instead of waving your hands in the general direction of “complexity.”

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Radical Markets

In 1997, I got my Ph.D. in social science from Caltech. The topic that drew me into grad school, and much of what I studied, was mechanism and institution design: how to redesign social practices and institutions. Economists and related scholars know a lot about this, much of which is useful for reforming many areas of life. Alas, the world shows little interest in these reforms, and I’ve offered our book The Elephant in the Brain: Hidden Motives in Everyday Life, as a partial explanation: most reforms are designed to give us more of what we say we want, and at some level we know we really want something else. While social design scholars would do better to work more on satisfying hidden motives, there’s still much useful in what they’ve already learned.

Oddly, most people who say they are interested in radical social change don’t study this literature much, and people in this area don’t much consider radical change. Which seems a shame; these tools are a good foundation for such efforts, and the topic of radical change has long attracted wide interest. I’ve tried to apply these tools to consider big change, such as with my futarchy proposal.

I’m pleased to report that two experts in social design have a new book, Radical Markets: Uprooting Capitalism and Democracy for a Just Society:

The book reveals bold new ways to organize markets for the good of everyone. It shows how the emancipatory force of genuinely open, free, and competitive markets can reawaken the dormant nineteenth-century spirit of liberal reform and lead to greater equality, prosperity, and cooperation. … Only by radically expanding the scope of markets can we reduce inequality, restore robust economic growth, and resolve political conflicts. But to do that, we must replace our most sacred institutions with truly free and open competition—Radical Markets shows how.

While I applaud the ambition of the book, and hope to see more like it, the five big proposals of the book vary widely in quality. They put their best feet forward, and it goes downhill from there. Continue reading "Radical Markets" »

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Social Innovation Disinterest Puzzle

Back in 1977, I started out college in engineering, then switched to physics, where I got a BS and MS. After that I spent nine years in computer research, at Lockheed and NASA. In physics, engineering, and software I saw that people are quite eager to find better designs, and that the world often pays a lot for them. As a result, it is usually quite hard to find even modesty better designs, at least for devices and mechanisms with modest switching costs.

Over time, I came to notice that many of our most important problems had cores causes in social arrangements. So I started to study economics, and found many simple proposed social innovations that could plausibly lead to large gains. And trying my own hand at looking for innovations, I found more apparently plausible gains. So in 1993 I switched to social science, and started a PhD program at the late age of 34, then having two kids age 0 and 2. (For over a decade after, I didn’t have much free time.)

I naively assumed that the world was just as eager for better social designs. But in fact, the world shows far less interest in better designs for social arrangements. Which, I should have realized, is a better explanation than my unusual genius for why it seemed so easy to find better social designs. But that raises a fundamental puzzle: why does the world seem so much less interested in social innovation, relative to innovation in physical and software devices and systems?

I’ve proposed the thesis of our new book as one explanation. But as many other explanations often come to people’s minds, I thought I might go over why I find them insufficient. Here goes: Continue reading "Social Innovation Disinterest Puzzle" »

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Ten Could be Twenty or More

Today is the official release date for our book The Elephant in the Brain: Hidden Motives in Everyday Life, and I can confirm that a copy sits on the shelf at my local B&N bookstore (across the aisle from where sits Age of Em, still on the shelf after 18 months). A Kindle version can be had for $14, and the hardback for $26 at Alibris.

On press coverage, back in July Publishers Weekly had a paragraph on it, the Boston Globe did an interview of me back then that they just released, Vice interviewed me recently so I expect that out soon, and I’m told that a Wall Street Journal review is forthcoming. Amazon now has 5 reviews, Goodreads has 7, and 3 reviews have appeared on blogs. And I’ve done 6 podcasts.

Though we see our main thesis as big and radical, so far all reviewers seem to have accepted it! (As did all of our 7 of the academic reviewers our publisher obtained internally a year ago.) That thesis is:

Our main goal is to demonstrate that hidden motives are common and important— that they’re more than a minor correction to the alternate theory that people mostly do things for the reasons that they give. For this purpose, we don’t need to be right about everything. In fact, we expect most readers to buy only about 70 percent of what we’re selling— and we’re OK with that.

We of course hope for more readers and press coverage. But we hope even more for intellectual engagement – people both agreeing and disagreeing with our particular arguments. And our highest hope is to inspire others to continue our research agenda. In our book we give detailed arguments for hidden motives in these ten areas of life:

Body Language, Laughter, Conversation, Consumption, Art, Charity, Education, Medicine, Religion, Politics.

But there are many more areas of life that we didn’t consider, and an awful lot of them are also plausible candidates for hidden motives. So if you have ambitions to be a social analyst who discovers important things about the social world, this seems to be a great opportunity for you. Go take some other area of life full of puzzling behaviors, and see if an alternate account of typical motives could better make sense of those puzzles.

We’ve already shown you how with our ten examples. To join our revolution, you just have to do the additional work in one more area. There’s social analysis gold in them thar hills. With your help, our ten examples could expand to twenty or more. And then we together would have pioneered a new understanding of human behavior.

Added 3 Jan: See my coauthor Kevin Simler’s “Ten Reasons To Read” our book.

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Authentic Signals

Many people (including me) claim that we eat food and drink water because without nutrition and fluids we would starve and dehydrate. Imagine this response:

No, people eat food because they are hungry, and drink water because they are thirsty. We don’t need abstract concepts like nutrition and dehydration to explain something so elemental as following our authentic feelings and desires.

Yes hunger and thirst are direct proximate causes of eating and drinking. But we are often interested in finding more distal explanations of such proximate causes. So almost no one objects to the nutrition and dehydration explanations of eating and drinking.

However, one of the most common criticisms I get about signaling explanations of human behavior is that we are instead just following authentic feelings and desires. As in this exchange:

Yes, people don’t need to consciously force themselves to express opinions on many topics. That habit comes quite naturally. Even so, we might want to explain that habit in terms of more basic distal forces.

I’m an economics professor, and the vast majority of economic papers and books that offer explanations for human behaviors don’t bother to distinguish if their explanations are mediated by conscious intentions or not. (In fact, most papers on any topic don’t take a stance on most possible distinctions related to their topic.) Economics are in fact famously wary (too wary I’d say) of survey data, as they fear conscious thoughts can mislead about economic behaviors.

Yet I’ve had even economics colleagues tell me that I should take more care, when I point out possible signaling explanations, to say if I am claiming that such signaling effects are consciously intended. But why would it be more important to distinguish conscious intentions in this context, compared to the rest of economics and social science?

My best guess is that what is going on here is that our social norms disapprove mildly of consciously intended signaling. Just as we aren’t supposed to brag, we also aren’t supposed to do things on purpose to make ourselves look good. It is okay to look good, but only as a side effect of doing things for other reasons. And as we usually claim other reasons for these behaviors, if we are actually doing them for signaling reasons we could also be accused of lying, which is also a norm violation.

Thus many see my signaling explanation proposals as accusing them personally of norm violations. At which point, they become vastly more interested in defending themselves against this accusation than in evaluating my general claims about human behavior. Perhaps if I were a higher status professor publishing in a prestigious journal, they might be reluctant to publicly challenge my claimed focus on distal explanations of general behavior patterns. But for mere tweets or blog posts by someone like me, they feel quite entitled to read me as accusing them of being bad people, unless I explicitly say otherwise. (And perhaps even then.) Sigh.

For the record, the degree of conscious intent of any behavior is a mildly interesting facet, but I’m less interested in it than are most people. This is in part because I’m inclined to give people less of a moral or legal pass on the harms resulting from behaviors if people do not consciously intend such consequences. It is just too easy for people to not notice such consequences, when they find it in their interest to not notice.

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Prepare for Nuclear Winter

If a 1km asteroid were to hit the Earth, the dust it kicked up would block most sunlight over most of the world for 3 to 10 years. There’s only a one in a million chance of that happening per year, however. Whew. However, there’s a ten times bigger chance that a super volcano, such as the one hiding under Yellowstone, might explode, for a similar result. And I’d put the chance of a full scale nuclear war at ten to one hundred times larger than that: one in ten thousand to one thousand per year. Over a century, that becomes a one to ten percent chance. Not whew; grimace instead.

There is a substantial chance that a full scale nuclear war would produce a nuclear winter, with a similar effect: sunlight is blocked for 3-10 years or more. Yes, there are good criticisms of the more extreme forecasts, but there’s still a big chance the sun gets blocked in a full scale nuclear war, and there’s even a substantial chance of the same result in a mere regional war, where only 100 nukes explode (the world now has 15,000 nukes).

I’ll summarize this as saying we face roughly a one in 10,000 chance per year of most all sunlight on Earth being blocked for 5 to 10 years. Which accumulates to become a 1% chance per century. This is about as big as your one in 9000 personal chance each year of dying in a car accident, or your one in 7500 chance of dying from poisoining. We treat both of these other risks as nontrivial, and put substantial efforts into reducing and mitigating such risks, as we also do for many much smaller risks, such as dying from guns, fire, drowning, or plane crashes. So this risk of losing sunlight for 5-10 years seems well worth reducing or mitigating, if possible.

Even in the best case, the world has only enough stored food to feed everyone for about a year. If the population then gradually declined due to cannibalism of the living, the population falls in half every month, and we’d all be dead in a few years. To save your family by storing ten years of food, you not only have to spend a huge sum now, you’d have to stay very well hidden or defended. Just not gonna happen.

Yeah, probably a few people live on, and so humanity doesn’t go extinct. But the only realistic chance most of us have of surviving in this scenario is to use our vast industrial and scientific abilities to make food. We actually know of many plausible ways to make more than enough food to feed everyone for ten years, even with no sunlight. And even if big chunks of the world economy are in shambles. But for that to work, we must preserve enough social order to make use of at least the core of key social institutions.

Many people presume that as soon as everyone hears about a big problem like this, all social institutions immediately collapse and everyone retreats to their compound to fight a war of all against all, perhaps organized via local Mad-Max-style warlords. But in places where this happens, everyone dies, or moves to places where something else happens.

Many take this as an opportunity to renew their favorite debate, on the right roles for government in society. But while there are clearly many strong roles for government to play in such a situation, it seems unlikely that government can smoothly step into all of the roles required here. Instead, we need an effective industry, to make food, collect its inputs, allocate its workers, and distribute its products. And we need to prepare enough to allow a smooth transition in a crisis; waiting until after the sunlights goes to try to plan this probably ends badly.

Thus while there are important technical aspects of this problem, the core of the problem is social: how to preserve functioning social institutions in a crisis. So I call to social scientist superheroes: we light the “bat signal”, and call on you to apply your superpowers. How can we keep enough peace to make enough food, so we don’t all starve, if Earth loses sunlight for a decade?

To learn more on making food without sunlight, see ALLFED.

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No One Rules The World

I’ve talked on my book Age of Em 79 times so far (#80 comes Saturday in Pisa, Italy). As it relies a lot on economics, while I mostly talk to non-econ audiences, I’ve been exposed a lot to how ordinary people react to economics. As I posted recently, one big thing I see a low confidence in any sort of social science to say anything generalizable about anything.

But the most common error I see is a lack of appreciation that coordination is hard. I hear things like:

If you asked most people today if they want a future like this, they’d say no. So how could it happen if most people don’t like it?

Their model seems to be that social outcomes are a weighted average of individual desires. If so, an outcome most people dislike just can’t happen. If you ask for a mechanism the most common choice is revolution: if there was some feature of the world that most people didn’t like, well of course they’d have a revolution to fix that. And then the world would be fixed. And not just small things: changes as big as the industrial or farming revolutions just wouldn’t happen if most people didn’t want them.

Now people seem to be vaguely aware that revolutions are hard and rare, that many attempted revolutions have failed, or succeeded but failed to achieve its stated aims, and that the world today has many features that majorities dislike. The world today has even more features where majorities feel unsure, not knowing what to think, because things are so complicated that it is hard to understand the feasible options and action consequences. Yet people seem to hold the future to a different standard, especially the far future.

Near-far theory (aka construal level theory) offers a plausible explanation for this different attitude toward the future. As we know a lot less detail about the future, we see it in a far mode, wherein we are more confident in our theories, see fewer relevant distinctions, and emphasize basic moral values relative to practical constraints. Even if the world around us seems too complex to understand and evaluate, issues and choices seem simpler and clearer regarding a distant future where in fact we can barely envision its outlines.

But of course coordination is actually very hard. Not only do most of us only dimly understand the actual range of options and consequences of our actions today, even when we do understand we find it hard to coordinate to achieve such outcomes. It is easier to act locally to achieve our local ends, but the net effect of local actions can result in net outcomes that most of us dislike. Coordination requires that we manage large organizations which are often weak, random, expensive, and out of control.

This seems especially true regarding the consequences of new tech. So far in history tech has mostly appeared whenever someone somewhere has wanted it enough, regardless of what the rest of the world thought. Mostly, no one has been driving the tech train. Sometimes we like the result, and sometimes we don’t. But no one rules the world, so these results mostly just happen either way.

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Social Science Critics

Many critics of Age of Em are critics of social science; they suggest that even though we might be able to use today’s physics or computer science to guess at futures, social science is far less useful.

For example At Crooked Timber Henry Farrell was “a lot more skeptical that social science can help you make predictions”, though he was more skeptical about thinking in terms of markets than in terms of “vast and distributed hierarchies of exploitation”, as these “generate complexities” instead of “ breaking them down.”

At Science Fact & Science Fiction Concatenation, Jonathan Cowie suggests social science only applies to biological creatures:

While Hanson’s treatise is engaging and interesting, I confess that personally I simply do not buy into it. Not only have I read too much SF to think that em life will be as prescriptive as Hanson portrays, but coming from the biological sciences, I am acutely aware of the frailties of the human brain hence mind (on a psychobiological basis). Furthermore, I am uncomfortable in the way that the social science works Hanson draws upon to support his em conclusions: it is an apples and oranges thing, I do not think that they can readily translate from one to the other; from real life sociobiological constructs to, in effect, machine code. There is much we simply do not know about this, as yet, untrodden land glimpsed from afar.

At Ricochet, John Walker suggests we can’t do social science if we don’t know detail stories of specific lives:

The book is simultaneously breathtaking and tedious. The author tries to work out every aspect of em society: the structure of cities, economics, law, social structure, love, trust, governance, religion, customs, and more. Much of this strikes me as highly speculative, especially since we don’t know anything about the actual experience of living as an em or how we will make the transition from our present society to one dominated by ems.

At his blog, Lance Fortnow suggests my social science assumes too much rationality:

I don’t agree with all of Hanson’s conclusions, in particular he expects a certain rationality from ems that we don’t often see in humans, and if ems are just human emulations, they may not want a short life and long retirement. Perhaps this book isn’t about ems and robots at all, but about Hanson’s vision of human-like creatures as true economic beings as he espouses in his blog. Not sure it is a world I’d like to be a part of, but it’s a fascinating world nevertheless.

At Entropy Chat List, Rafal Smigrodzki suggests social science doesn’t apply if ems adjust their brain design:

My second major objection: Your pervasive assumption that em will remain largely static in their overall structure and function. I think this assumption is at least as unlikely as the em-before-AI assumption. Imagine .. you have the detailed knowledge of your own mind, the tools to modify it, and the ability to generate millions of copies to try out various modifications. .. you do analyze this possibility, you consider some options but in the end you still assume ems will be just like us. Of course, if ems are not like us, then a lot of the detailed sociological research produced on humans would not be very applicable to their world and the book would have to be shorter, but then it might be a better one. In one chapter you mention that lesbian women make more money and therefore lesbian ems might make money as well. This comes at the end of many levels of suspension of disbelief, making the sociology/gender/psychology chapters quite exhausting.

At his blog, J Storrs Hall said something similar:

Robin’s scenario precludes some of these concerns by being very specific to a single possibility: that we have the technology to copy off any single particular human brain, we don’t understand them well enough to modify them arbitrarily. Thus they have to operated in a virtual reality that is reasonably close to a simulated physical world. There is a good reason for doing it this way, of course: that’s the only uploading scenario in which all the social science studies and papers and results and so forth can be assumed to still apply.

Most social scientists, and especially most economists, don’t see what they have learned as being quite so fragile. Yes it is nice to check abstract theories against concrete anecdotes, but in fact most who publish papers do little such checking, and their results only suffer modestly from the lack. Yes being non-biological, or messing a bit with brain design, may make some modest differences. But most social science theory just isn’t that sensitive to such details. As I say in the book:

Our economic theories apply reasonably well not only to other classes and regions within rich nations today, but also to other very different nations today and to people and places thousands of years ago. Furthermore, formal economic models apply widely even though quite alien creatures usually populate them, that is, selfish rational strategic agents who never forget or make mistakes. If economic theory built using such agents can apply to us today, it can plausibly apply to future ems.

The human brain is a very large complex legacy system whose designer did not put a priority on making it easy to understand, modify, or redesign. That should greatly limit the rate at which big useful redesign is possible.

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My Caplan Turing Test

At lunch today Bryan Caplan and I dug a bit into our disagreement, and now I’ll try to summarize his point of view. He can of course correct me.

Bryan sees sympathy feelings as huge influences on social outcomes. Not just feelings between people who know each other well, but also distant feelings between people who have never met. For example, if not for feelings of sympathy:

  1. Law and courts would often favor different disputants.
  2. Free workers would more often face harsh evaluations, punishments, and firing.
  3. Firm owners and managers would know much better which workers were doing good jobs.
  4. The US would invade and enslave Canada tomorrow.
  5. At the end of most wars, the victors would enslave the losers.
  6. Modern slaves would earn their owners much more than they would have as free workers.
  7. In the past, domestic, artisan, and city slaves, who were treated better than field slaves, would have been treated much more harshly.
  8. The slave population would have fallen less via gifts or purchase of freedom.
  9. Thus most of the world population today would be slaves.

These views are, to me, surprisingly different from the impression I get from reading related economics literatures. Bryan says I may be reading the wrong ones, but he hasn’t yet pointed me to the correct ones. As I read them, these usual economics literatures give different impressions:

  • Law and economics literature suggests efficiency usual decides who wins, with sympathy distortions having a real but minor influence.
  • Organization theory literature suggests far more difficulties in motivating workers and measuring their performance.
  • Slavery literature suggests slaves doing complex jobs were treated less harshly for incentive reasons, and would not have earned much more if treated more harshly. Thus modern slaves would also not earn much more as slaves.

Of course even if Bryan were right about all these claims, he needn’t be right in his confident opinion that the vast majority of biological humans will have about as much sympathy for ems as they do for mammals, and thus treat ems as harshly as we treat most mammals.

This sympathy-driven view doesn’t by itself predict Caplan’s strong (and not much explained) view that ems would also be very robot-like. But perhaps we might add to it a passion for domination – people driven by feelings to treat nicely creatures they respect might also be driven by feelings to dominate creatures they do not respect. Such a passion for dominance might induce biological humans to force ems to into ultra docility, even if that came at a productivity cost.

Added 28July2016: Caplan grades my summary of his position. I’m mostly in the ballpark, but he elaborates a bit on why he thinks em slaves would be docile:

Docile slaves are more profitable than slaves with attitude, because owners don’t have to use resources to torture and scare them into compliance.  That’s why owners sent rebellious slaves to “breakers”: to transform rebellious slaves into docile slaves.  Sci-fi is full of stories about humans genetically engineered to be model slaves.  Whole brain emulation is a quicker route to a the same destination.  What’s the puzzle?

For docility to be such a huge priority, relative to other worker features, em rebellion must happen often and impose big frequent costs. Docility doesn’t seem to describe our most productive workers today well, nor does it seem well suited when you want workers to be creative, think carefully, take the initiative, or persuade and inspire others. Either way, either frequent costly rebellions or extreme docility, create big disadvantages of slaves relative to free workers, and so argues against most ems being slaves.

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